When developers deploy applications to an application server they are hoping to leverage the various facilities of the environment to achieve the best application performance. This application performance is typically measured in terms of response time, transactions per second, throughput, etc. The application server vendors, in turn, do their best to optimize their servers to provide the best performance possible out of the box.
Performance tuning of applications running in an application server may potentially involve the modification of multiple configuration parameters such as thread pool size, connection pool size, transaction timeout period, various Java Virtual Machine (JVM) parameters, and component configuration items.
However, each application deployed to an application server has its own unique characteristics. For example, the mixture of web based components, Enterprise JavaBeans (EJBs), and back-end resources, and the manner in which these components are accessed, can have dramatic effects on the system's performance. Therefore, each application deployment requires a tuning phase on a staging platform in order to find the optimum settings for various platform parameters, such as the Java Virtual machine parameters, the application server configuration settings, etc., as well as some application dependent settings. This phase may involve the use of third party tools, which may be very expensive, and multiple application restarts, which prolong the process. In addition, multiple software tools such as web load generators etc. are generally required to perform these operations. This performance tuning process is currently the domain of engineers with expertise in the deployed application, the application server, networking, and hardware. All of this results in an application tuning process that is expensive and time consuming. A need arises for an technique by which the application tuning process can be made simpler and easier, so that it can be performed by less skilled individuals and yet be performed more quickly by those less skilled individuals.